Motion of animated streamlets appears to surpass their graphical alterations in human visual detection of vector field maxima

ABSTRACT

Animations have become a frequently utilized illustration technique on maps but changes in their graphical loading remain understudied in empirical geovisualization and cartographic research. Animated streamlets have gained attention as an illustrative animation technique and have become popular on widely viewed maps. We conducted an experiment to investigate how altering four major animation parameters of animated streamlets affects people’s reading performance of field maxima on vector fields. The study involved 73 participants who performed reaction-time tasks on pointing maxima on vector field stimuli. Reaction times and correctness of answers changed surprisingly little between visually different animations, with only a few occasional statistical significances. The results suggest that motion of animated streamlets is such a strong visual cue that altering graphical parameters makes only little difference when searching for the maxima. This leads to the conclusion that, for this kind of a task, animated streamlets on maps can be designed relatively freely in graphical terms and their style fitted to other contents of the map. In the broader visual and geovisual analytics context, the results can lead to more generally hypothesizing that graphical loading of animations with continuous motion flux could be altered without severely affecting their communicative power.     

基于S波段双极化雷达的变分法的定量降水估计算法

基于比差分传播相移(K_DP)的降水估计算法R(K_DP)相较于传统基于水平反射率因子(Z_H)的算法R(Z_H)的表现更优。在雷达实际运行中,由于随机误差和后向散射相位(backscattering phase)的影响,可能出现负的K_DP。运用一种基于变分的雷达定量降水估计混合算法(V-RQPE)。该算法用变分拟合方法重构差分相位(Φ_DP),用一种新的稳健的边界条件求解方法,在消除随机误差的同时获得非负的K_DP,进而进行降水估计。随后我们使用2017年5月7日广州S波段雷达的回波数据和地面雨量站观测数据进行验证,同时使用了六种不同的算法进行对比,结果显示,在1小时累计降水估计中,V-RQPE表现最好,在24小时累计降水估计中,V-RQPE和基于变分拟合的K_DP的降水估计算法(R-VKDP)表现最好,实验结果表明变分拟合方法对雷达降水估计能力有显著提升。      

Box-Cox正态转换在长江子流域极端降水气候事件判定中的应用

利用1961-2017年长江流域700个气象站点逐月降水资料计算长江流域9个子流域面雨量,采用基于Box-Cox正态分布转换后的百分位法对长江流域不同时间长度的极端降水气候事件阈值进行界定。结果表明,在数据序列长度发生变化的情况下,面雨量序列经Box-Cox正态转换后,计算得到的极端降水气候事件阈值的变化相较于常规百分位法明显减小,具有更为稳健的特性,从而使得相应极端降水气候事件个例的挑选更为稳定。根据该方法得到的阈值,对2018年汛期(6-8月)长江各子流域极端降水气候事件进行判定,岷沱江流域发生了极端多雨气候事件,而长江干流重庆-宜昌段、汉江及中游干流区间发生了极端少雨气候事件。     

基于区域自动站数据的兰州地区降水精细化特征

基于2012—2019年兰州地区146个区域自动气象站小时降水数据,从不同时间尺度分析兰州地区近8 a降水精细化特征。结论如下:(1)2012—2019年,兰州地区年均降水量总体呈"北少南多、外多内少"的空间分布特征;年降水量具有明显的年际变化,2018年降水异常偏多46%,而2015、2017年降水异常偏少,尤其2015年偏少30%。(2)兰州地区降水主要集中在7—8月,受环流形势影响,7—8月南部降水明显多于北部,其余月份南北降水差异不明显。(3)兰州地区降水量和降水范围分别表现为"朝少夕多"、"夜大日小"的日变化特征;受海拔高度影响,城区降水量总体比山区小,且因热岛效应,城区降水主要集中在午后至傍晚前后,多为对流性降水,而山区降水日分布较为均匀,整体日波动较小。(4)安宁区短时强降水发生频次最高,但短时强降水频发的站点出现在皋兰县六合站和永登县徐家磨村站,永登县是兰州地区短时强降水预报需重点关注的地区。     

基于区域自动站数据的兰州地区降水精细化特征

基于2012—2019年兰州地区146个区域自动气象站小时降水数据,从不同时间尺度分析兰州地区近8 a降水精细化特征。结论如下:(1)2012—2019年,兰州地区年均降水量总体呈"北少南多、外多内少"的空间分布特征;年降水量具有明显的年际变化,2018年降水异常偏多46%,而2015、2017年降水异常偏少,尤其2015年偏少30%。(2)兰州地区降水主要集中在7—8月,受环流形势影响,7—8月南部降水明显多于北部,其余月份南北降水差异不明显。(3)兰州地区降水量和降水范围分别表现为"朝少夕多"、"夜大日小"的日变化特征;受海拔高度影响,城区降水量总体比山区小,且因热岛效应,城区降水主要集中在午后至傍晚前后,多为对流性降水,而山区降水日分布较为均匀,整体日波动较小。(4)安宁区短时强降水发生频次最高,但短时强降水频发的站点出现在皋兰县六合站和永登县徐家磨村站,永登县是兰州地区短时强降水预报需重点关注的地区。     

Change in Precipitation over the Tibetan Plateau Projected by Weighted CMIP6 Models

Precipitation over the Tibetan Plateau (TP) is important to local and downstream ecosystems. Based on a weighting method considering model skill and independence, changes in the TP precipitation for near-term (2021–40), mid-term (2041–60) and long-term (2081–2100) under shared socio-economic pathways (SSP1-1.9, SSP1-2.6, SSP2-4.5, SSSP3-7.0, SSP5-8.5) are projected with 27 models from the latest Sixth Phase of the Couple Model Intercomparison Project. The annual mean precipitation is projected to increase by 7.4%–21.6% under five SSPs with a stronger change in the northern TP by the end of the 21st century relative to the present climatology. Changes in the TP precipitation at seasonal scales show a similar moistening trend to that of annual mean precipitation, except for the drying trend in winter precipitation along the southern edges of the TP. Weighting generally suggests a slightly stronger increase in TP precipitation with reduced model uncertainty compared to equally-weighted projections. The effect of weighting exhibits spatial and seasonal differences. Seasonally, weighting leads to a prevailing enhancement of increase in spring precipitation over the TP. Spatially, the influence of weighting is more remarkable over the northwestern TP regarding the annual, summer and autumn precipitation. Differences between weighted and original MMEs can give us more confidence in a stronger increase in precipitation over the TP, especially for the season of spring and the region of the northwestern TP, which requires additional attention in decision making.     

影响华南汛期持续性强降水年际变化的大气环流和海温异常

利用1961—2017年中国地面观测站日降水资料、全球大气多要素和海表温度月资料,分析华南区域持续性强降水过程的气候特征,诊断并比较与华南前汛期、后汛期区域持续性强降水年际变化相关的大气环流和海表温度异常特征。结果表明,3—12月华南都可能出现持续性强降水过程,其中汛期4—9月的占了94.4%。伴随着区域持续性强降水的年际变化,华南本地垂直上升运动显著异常是前汛期和后汛期的共同点,但前汛期、后汛期在华南及周边环流异常、水汽输送来源以及海温异常分布等方面都存在一定差异。在前汛期华南区域持续性强降水偏重年,赤道西太平洋区域海温偏低,由于大气罗斯贝波响应使西太平洋副热带高压偏强,热带西太平洋向华南区域水汽输送加强,从而有利于区域持续性强降水偏重。后汛期华南区域持续性强降水偏重年的海温异常分布是赤道中东太平洋区域正异常、东印度洋至西太平洋暖池区负异常,海温异常通过西北太平洋副热带高压、南海热带季风强度、水汽输送和垂直环流等多方面,导致后汛期区域持续性强降水偏重。      

中国60城市站1901—2019年日降水数据集的构建

近年来中国区域降水的极端化问题得到学术界的广泛关注,有关研究也获得了大量成果。但是,目前国内外常用的高分辨率降水资料序列多从1951年左右开始,普遍缺少20世纪早期中国的逐日降水资料,对于近一百多年中国极端降水变化特征及其机理,目前还不清楚。基于多来源的1901—1950年原始观测报表数字化逐日降水资料,补充先前未录入的“无降水”和缺测数据,研发质量控制方案并开展质量控制,补充录入检出的缺失和错误数据并再次质控,结合1951年以来的现代降水日值资料,建立中国60个城市站1901—2019年降水日值数据集。数据集评估结果显示,早期中国东部地区的台站较为密集,数据完整性和正确性较好,但中国西部的台站数量少且完整性和正确性偏低。本数据集构建的年总降水量累积值序列与已有的月降水量数据基本一致。基于该数据集,研究发现重庆站近百年来的降水未出现显著的趋势性变化。该数据集使后续分析研究中国极端降水的百年尺度长期变化特征成为可能。     

The increasing predominance of extreme precipitation in Southwest China since the late 1970s

Extreme precipitation events cause severe environmental and societal damage worldwide. Southwest China (SWC) is sensitive to such effects because of its overpopulation, underdevelopment, and fragile ecosystems. Using daily observations from 108 rain-gauge stations, the authors investigated the frequency of extreme precipitation events and their contribution to total precipitation in SWC since the late 1970s. Results indicate that total precipitation is decreasing insignificantly, but rainfall-events frequency is decreasing significantly, whereas the region is experiencing more frequent and intense extreme precipitation events. Note that although fewer stations are statistically significant, about 60% of the rain-gauge stations show an increasing trend in the frequency and intensity of extreme precipitation. Furthermore, there is an increasing trend in the contribution of total extreme precipitation to total precipitation, with extreme precipitation becoming dominant in the increasingly arid SWC region. The results carry important implications for policymakers, who should place greater emphasis on extreme precipitation and associated floods and landslides when drafting water-resource management policies.摘要本文分析了中国西南20世纪70年代末以来极端降水事件的频率, 强度及其对总降水的贡献. 结果表明, 该地区约60%的降水站点极端降水的频率和强度正在增加, 而大多数站点总降水频率明显减少. 同时极端降水总量对总降水量的贡献有显著增加的趋势, 极端降水在日益干旱的中国西南地区变得更具主导性. 研究结果提醒应更加重视极端降水及其可能引发的次生灾害, 如洪水, 山体滑坡等.     

华南复杂地形下GRAPES_Meso3km对流尺度模式前汛期精细化降水预报评估

为深入认识GRAPES_Meso(Global/Regional Assimilation and Prediction System)3 km对流尺度区域模式对华南前汛期精细化降水的预报性能,为模式改进及业务应用提供参考依据,利用广东省86个站点逐小时观测降水资料和国家气象信息中心多源融合降水资料,针对广东省复杂地形特点,结合距海岸线的远近及站点地形特点,将86个站划分为沿海东部、沿海西部和内陆地区三个子区域,采用二分类降水预报检验方法,定量评估了2020年5月18日—6月18日华南前汛期降水预报效果。结果显示,GRAPES_Meso 3 km模式精细化降水预报技巧受广东复杂地形影响较大,广东沿海东部和内陆地区24 h时累积降水的小雨、中雨、大雨量级预报成功指数(Threat Score,TS)、公平成功指数(Equitable Threat Score,ETS)评分高于沿海西部地区,尽管暴雨预报评分具有此相同特征,但三个子区域的暴雨预报评分总体较低;从3 h累积降水预报评分看,沿海东部、沿海西部及内陆地区等三个子区域存在明显的日变化特征,但是沿海东部及西部与内陆地区表现有所不同,沿海东部和西部降水预报评分夜间较低(预报偏差偏高),白天相对较高(预报偏差偏低),而内陆地区则是夜间较高(预报偏差偏低),白天相对较低(预报偏差偏高)。沿海西部预报评分相对较低的原因是由于检验时段内广东地区存在一个弱的风切变,而沿海西部大部分地区正好处于切变线南侧的温度高值区控制,但模式模拟该区域的日平均温度较实况偏低,导致沿海西部模式预报降水空报较多,降低其降水预报技巧。